Tabea Rebafka
Position
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Contact
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tabea.rebafka AT sorbonne-universite.fr Office
Tour 15-16, 2ème étage, bureau 214 Phone++ 33 - (0)1 44 27 80 05 Postal address
LPSM
Sorbonne Université |
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Research Activity
Research Topics
- Random graph models
- Statistical and ML algorithms
- Nonparametric estimation
Research projects
- ANR BACKUP starting in 2024
- ANR, EcoNet - Advanced statistical modelling of ecological networks, since 2018
- Défi Santé numérique (INSERM/CNRS), Modelling metabolism of intestinal
microbiome by multi-omics statistical data integration avec l'équipe Nutriomics, 2019
- ANR, BASICS - Bayesian nonparametrics, uncertainty quantification and random structures, 2017-2022
- PEPS, Spectral methods for machine learning with Malika Kharouf and Nataliya Sokolovska. Project Coordinator. 2017
- PEPS, Random matrix theory for machine learning with Malika Kharouf and Nataliya Sokolovska. Project Coordinator. 2016
PHD Students
- Ariane Marandon, co-supervised with Etienne Roquain and Nataliya Sokolovska, 2020-2023.
- Sara Rejeb, thèse CIFRE avec Safran Aircraft Engines, co-supervised with Catherine Duveau, 2020-2023.
- Arsen Sultanov, co-supervised with Jean-Claude Crivello (ICMPE) and Nataliya Sokolovska, since 2021.
- Roland Sogan, co-supervised with Fanny Villers, since 2023.
Publications
Journal articles
- Data-driven score-based models for generating stable structures with adaptive crystal cells. With Arsen Sultanov, Jean-Claude Crivello and Nataliya Sokolovska. Accepted for publication in Journal of Chemical Information and Modeling. pdf
- Model-based clustering of multiple networks with a hierarchical algorithm. Statistics and Computing, 34:32 (2024). pdf
- False clustering rate control in mixture models. With Ariane Marandon, Etienne Roquain and Nataliya Sokolovska preprint
- Self-organizing maps for exploration of partially observed data and imputation of missing values. With Sara Rejeb and Catherine Duveau. Chemometrics and Intelligent Laboratory Systems, 231:104653 (2022). pdf
- Powerful multiple testing of paired null hypotheses using a latent graph model. With Etienne Roquain and Fanny Villers.
Electronic Journal of Statistics, Vol. 16, Issue 1, 2796-2858 (2022).
pdf
- Properties of the Stochastic Approximation EM Algorithm with Mini-batch Sampling. With Estelle Kuhn and Catherine Matias. Statistics and Computing, 30, 1725-1739 (2020) pdf
- A semiparametric extension of the stochastic block model for longitudinal networks. With Catherine Matias and Fanny Villers.
Biometrika, Vol. 105, Iss. 3, p. 665 - 680 (2018).
pdf.
R code ppsbm-files.zip
- Discussion on `Sparse graphs using exchangeable random measures' by F. Caron and E. B. Fox. With Ismael Castillo. Journal of the Royal Statistical Society, Series B, Vol. 79, No. 5, p. 1295 - 1366 (2017).
pdf
- Nonparametric weighted estimators for biased data. With Fabienne Comte. Journal of Statistical Planning and Inference, 174, 104-128 (2016).
pdf
- Nonparametric Estimation of the Mixing Density Using Polynomials. With François Roueff. Mathematical Methods of Statistics, Vol. 24, No. 3, 200-224 (2015).
pdf
- OMP-type Algorithm with Structured Sparsity Patterns for Multipath Radar Signals. With Céline Lévy-Leduc and Maurice Charbit. Technical report (2011).
pdf
- Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors. With Fabienne Comte. Electronic Journal of Statistics, 6, 2002-2037 (2012).
pdf
- Information bounds and MCMC parameter estimation for the pile-up model. With
François Roueff and Antoine Souloumiac. Journal of Statistical Planning and Inference, 141, 1–16 (2011).
pdf
- A Corrected Likelihood Approach for the Pile-Up Model with Application to
Fluorescence Lifetime Measurements Using Exponential Mixtures. With François
Roueff and Antoine Souloumiac. The International Journal of Biostatistics, Vol. 6, Iss. 1, Article 9 (2010).
pdf
- Bootstrap-based tolerance intervals for application to method validation. With
Stéphan Clémençon and Max Feinberg. Chemometrics and Intelligent Laboratory
Systems, 89, 69–81 (2007).
pdf
Patent
- Procédé d’estimation des paramètres de la distribution des temps de réponse
de particules d’un système, appliqué notamment aux mesures de fluorescence.
With François Roueff and Antoine Souloumiac. Patent Number 09 00524, February
2009.
Proceedings and Conferences
- Application of machine learning for prediction of turbofan's airflow. With S. Rejeb and C. Duveau.
Turbo Expo 2023, Boston, June, 2023.
- False clustering rate control in mixture models.
With A. Marandon, E. Roquain and N. Sokolovska. In: MCP Conference, Bremen, Germany, 2022.
- Generating new crystal structures with statistical methods.
With A. Sultanov, J.-C. Crivello and N. Sokolovska. In: Journées de Statistique de la SFdS, Lyon, 2022.
- False clustering rate control in mixture models.
With A. Marandon, E. Roquain and N. Sokolovska. In: Journées de Statistique de la SFdS, Lyon, 2022.
- Cartes auto-organisatrices pour l'exploration de données partiellement observées et l'imputation de données manquantes.
With S. Rejeb and C. Duveau. In: Journées de Statistique de la SFdS, Lyon, 2022.
- Stochastic block model for multiple networks.
Bernoulli-IMS World Congress in Probability and Statistics, July, 2021.
- Stochastic block model for multiple networks.
ISI World Statistics Congress, July, 2021.
- Inférence de graphe avec contrôle du taux de faux positifs.
With Fanny Villers and Etienne Roquain. In: Journées de Statistique de la SFdS, 2020. pdf
- Eigenrange: A Robust Spectral Method for Dimensionality Reduction. With Malika Kharouf and Nataliya Sokolovska. EUSIPCO, 2018.
pdf
- Estimation adaptative de densité dans un modèle de transformation nonlinéaire.
With Fabienne Comte. In: 43e Journées de Statistique de la SFdS, Gammarth, Tunisie. pdf
- Regularization Methods for Intercepted Radar Signals.
With Céline-Lévy Leduc and Maurice Charbit. In: IEEE Radar Conference 2011, Kansas City, USA.
- Désempilement de mesures de temps de réponse par un algorithme E.M. modifié.
With François Roueff and Antoine Souloumiac. In: GRETSI 2009: 22ème colloque sur
le traitement du signal et des images, Dijon, France.
pdf
- An MCMC approach for estimating a fluorescence lifetime with pile-up
distortion. In: GRETSI 2007: 21ème colloque sur le traitement du signal et des
images, Troyes, France. pdf
Thesis
- Statistical learning on networks and more.
Habilitation à diriger des recherches defended on 22 June 2023.
pdf
- Estimation in the Pile-Up Model with Application to Fluorescence
Lifetime Measurements.
Ph.D. thesis defended on 23 October 2009.
pdf
Code
- R package graphclust released on CRAN, 2023. Hierarchical graph clustering for a collection of networks.
- R package missSOM released on CRAN. With Sara Rejeb and Catherine Duveau, 2021. Self-organizing maps with built-in missing-data imputation.
- R code for reproducibility of results of the article Graph inference with clustering and false discovery rate control. With Fanny Villers and Etienne Roquain, 2020.
- R package noisySBM released on CRAN. With Fanny Villers and Etienne Roquain, 2020. Implementation of the methods presented in the article Graph inference with clustering and false discovery rate control.
- R and Matlab code for the article
Properties of the Stochastic Approximation EM Algorithm with Mini-batch Sampling. With Estelle Kuhn and Catherine Matias. Statistics and Computing (2020) tgz
- R code for the variational EM-algorithm for the Poisson process stochastic block model with Catherine Matias and Fanny Villers: ppsbm-files.zip This file contains the analysis of three datasets with PPSBM.
- R package ppsbm released on CRAN. With Daphné Giorgi, Catherine Matias and Fanny Villers, 2018. This package contains the optimized R code for PPSBM.
Enseignement
Formation continue
-
Introduction au Machine Learning et au Deep Learning avec Python, Formation Entreprise CNRS. Prochaine édition : du 19 au 21 juin 2024.
Voici la
Page de la formation et la
Fiche d'information
Notes de cours
- Analyse statistique de graphes, M2 de Statistique
Notes de cours 2021 Book
Données pour les TP TP 1
-
Probability Refresher, Master Data Science for Business, X-HEC
Textbook pdf
Slides Chapter 1, Chapter 2 1st part, 2nd part, Chapter 3, Chapter 4, Chapter 5
-
Probabilités numériques et statistique computationnelle, M1,
avec Vincent Lemaire
Poly 2021 pdf
Notebook 6, Estimation de paramètres de la loi Gamma, NB6_sujet.ipynb, NB6_sujet.html
Notebook 7, Bootstrap, NB7_sujet.ipynb, NB7_sujet.html
Notebook 8, Le package boot, NB8_sujet.ipynb, NB8_sujet.html
Notebook 9, Modèle de mélange, NB9_sujet.ipynb, NB9_sujet.html
Notebook 10, Algorithme EM pour mélange gaussien, NB10_sujet.ipynb, NB10_sujet.html
Notebook 11, Echantillonneur de Gibbs pour mélange gaussien, NB11_sujet.ipynb, NB11_sujet.html
- Aléatoire - MAP361, Ecole polytechnique
Feuilles d'exercices 2020 PC 1,
PC 2,
PC 3,
PC 4,
PC 5,
PC 6,
PC 7,
PC 8,
PC 9
-
Statistical Modeling with R, Master in the Mathematical Sciences, AIMS Sénégal, 2018
Slides Chapter 1,
Chapter 2,
Chapter 3,
Chapter 4,
Chapter 5
Computer Labs Lab 1, Lab 2, Lab 3,
Exercises Series 1, Series 2, Series 3
Assignment zip
-
Statistique, 4M015, M1, version 2017, Partie II
- Statistique appliquée, M1, version 2015, Partie I et II
Notebooks d'anciens cours
- Statistique numérique (3M248)
Notebook 1, Rappels et prise en main, NB1_Series.ipynb, NB1_Series.html
Notebook 2, Tableaux de données, NB2_Dataframe.ipynb, NB2_Dataframe.html
Notebook 3, Figures, NB3_Figures.ipynb, NB3_Figures.html
Notebook 4, Statistique descriptive univariée, NB4_stat_descr_uni.ipynb, NB4_stat_descr_uni.html
Notebook 5, Statistique descriptive pour des données bivariées, NB5_stat_descr_bivarie.ipynb, NB5_stat_descr_bivarie.html
Notebook 6, Variables qualitatives et indépendance, NB6_variables_qualitatives.ipynb, NB6_variables_qualitatives.html
Notebook 7, Analyse en composantes principales, NB7_ACP.ipynb, NB7_ACP.html
Notebook 8, Interprétation de l'ACP, NB8_ACP_bis.ipynb, NB8_ACP_bis.html
- Statistique (4M015)
Prise en main de R pdf
Notebook 1, Notebook R, vecteurs et génération de variables aléatoires, Notebook_1.ipynb, Notebook_1.html
Notebook 2, Type de données, Notebook_2.ipynb, Notebook_2.html , Données zip
Notebook 3, Représentations graphiques des données, Notebook_3.ipynb, Notebook_3.html , données anorexie
Programmation en R pdf
Notebook 4, Simulations Monte-Carlo, Notebook_4.ipynb, Notebook_4.html
Notebook 5, Simulations Monte-Carlo (suite), Notebook_5.ipynb, Notebook_5.html
Notebook 6, Régression simple, Notebook_6.ipynb, Notebook_6.html , Données ozone, cathedral
Notebook 7, Régression multiple, Notebook_7.ipynb, Notebook_7.html , Données poidsnaiss
Notebook 8, Analyse de la variance, Notebook_8.ipynb, Notebook_8.html
Other
Exposé pour des jeunes mathématicien·ne·s
-
Mathematic Park , exposé du 25 novembre 2023 intitulé Tous connectés sur les réseaux sociaux.
Quels outils mathématiques pour les analyser ?
Voici les
slides et le
notebook R
- Ariane Marandon, co-supervised with Etienne Roquain and Nataliya Sokolovska, 2020-2023.
- Sara Rejeb, thèse CIFRE avec Safran Aircraft Engines, co-supervised with Catherine Duveau, 2020-2023.
- Arsen Sultanov, co-supervised with Jean-Claude Crivello (ICMPE) and Nataliya Sokolovska, since 2021.
- Roland Sogan, co-supervised with Fanny Villers, since 2023.
Publications
Journal articles
- Data-driven score-based models for generating stable structures with adaptive crystal cells. With Arsen Sultanov, Jean-Claude Crivello and Nataliya Sokolovska. Accepted for publication in Journal of Chemical Information and Modeling. pdf
- Model-based clustering of multiple networks with a hierarchical algorithm. Statistics and Computing, 34:32 (2024). pdf
- False clustering rate control in mixture models. With Ariane Marandon, Etienne Roquain and Nataliya Sokolovska preprint
- Self-organizing maps for exploration of partially observed data and imputation of missing values. With Sara Rejeb and Catherine Duveau. Chemometrics and Intelligent Laboratory Systems, 231:104653 (2022). pdf
- Powerful multiple testing of paired null hypotheses using a latent graph model. With Etienne Roquain and Fanny Villers. Electronic Journal of Statistics, Vol. 16, Issue 1, 2796-2858 (2022). pdf
- Properties of the Stochastic Approximation EM Algorithm with Mini-batch Sampling. With Estelle Kuhn and Catherine Matias. Statistics and Computing, 30, 1725-1739 (2020) pdf
- A semiparametric extension of the stochastic block model for longitudinal networks. With Catherine Matias and Fanny Villers. Biometrika, Vol. 105, Iss. 3, p. 665 - 680 (2018). pdf. R code ppsbm-files.zip
- Discussion on `Sparse graphs using exchangeable random measures' by F. Caron and E. B. Fox. With Ismael Castillo. Journal of the Royal Statistical Society, Series B, Vol. 79, No. 5, p. 1295 - 1366 (2017). pdf
- Nonparametric weighted estimators for biased data. With Fabienne Comte. Journal of Statistical Planning and Inference, 174, 104-128 (2016). pdf
- Nonparametric Estimation of the Mixing Density Using Polynomials. With François Roueff. Mathematical Methods of Statistics, Vol. 24, No. 3, 200-224 (2015). pdf
- OMP-type Algorithm with Structured Sparsity Patterns for Multipath Radar Signals. With Céline Lévy-Leduc and Maurice Charbit. Technical report (2011). pdf
- Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors. With Fabienne Comte. Electronic Journal of Statistics, 6, 2002-2037 (2012). pdf
- Information bounds and MCMC parameter estimation for the pile-up model. With François Roueff and Antoine Souloumiac. Journal of Statistical Planning and Inference, 141, 1–16 (2011). pdf
- A Corrected Likelihood Approach for the Pile-Up Model with Application to Fluorescence Lifetime Measurements Using Exponential Mixtures. With François Roueff and Antoine Souloumiac. The International Journal of Biostatistics, Vol. 6, Iss. 1, Article 9 (2010). pdf
- Bootstrap-based tolerance intervals for application to method validation. With Stéphan Clémençon and Max Feinberg. Chemometrics and Intelligent Laboratory Systems, 89, 69–81 (2007). pdf
Patent
- Procédé d’estimation des paramètres de la distribution des temps de réponse de particules d’un système, appliqué notamment aux mesures de fluorescence. With François Roueff and Antoine Souloumiac. Patent Number 09 00524, February 2009.
Proceedings and Conferences
- Application of machine learning for prediction of turbofan's airflow. With S. Rejeb and C. Duveau. Turbo Expo 2023, Boston, June, 2023.
- False clustering rate control in mixture models. With A. Marandon, E. Roquain and N. Sokolovska. In: MCP Conference, Bremen, Germany, 2022.
- Generating new crystal structures with statistical methods. With A. Sultanov, J.-C. Crivello and N. Sokolovska. In: Journées de Statistique de la SFdS, Lyon, 2022.
- False clustering rate control in mixture models. With A. Marandon, E. Roquain and N. Sokolovska. In: Journées de Statistique de la SFdS, Lyon, 2022.
- Cartes auto-organisatrices pour l'exploration de données partiellement observées et l'imputation de données manquantes. With S. Rejeb and C. Duveau. In: Journées de Statistique de la SFdS, Lyon, 2022.
- Stochastic block model for multiple networks. Bernoulli-IMS World Congress in Probability and Statistics, July, 2021.
- Stochastic block model for multiple networks. ISI World Statistics Congress, July, 2021.
- Inférence de graphe avec contrôle du taux de faux positifs. With Fanny Villers and Etienne Roquain. In: Journées de Statistique de la SFdS, 2020. pdf
- Eigenrange: A Robust Spectral Method for Dimensionality Reduction. With Malika Kharouf and Nataliya Sokolovska. EUSIPCO, 2018. pdf
- Estimation adaptative de densité dans un modèle de transformation nonlinéaire. With Fabienne Comte. In: 43e Journées de Statistique de la SFdS, Gammarth, Tunisie. pdf
- Regularization Methods for Intercepted Radar Signals. With Céline-Lévy Leduc and Maurice Charbit. In: IEEE Radar Conference 2011, Kansas City, USA.
- Désempilement de mesures de temps de réponse par un algorithme E.M. modifié. With François Roueff and Antoine Souloumiac. In: GRETSI 2009: 22ème colloque sur le traitement du signal et des images, Dijon, France. pdf
- An MCMC approach for estimating a fluorescence lifetime with pile-up distortion. In: GRETSI 2007: 21ème colloque sur le traitement du signal et des images, Troyes, France. pdf
Thesis
- Statistical learning on networks and more. Habilitation à diriger des recherches defended on 22 June 2023. pdf
- Estimation in the Pile-Up Model with Application to Fluorescence Lifetime Measurements. Ph.D. thesis defended on 23 October 2009. pdf
Code
- R package graphclust released on CRAN, 2023. Hierarchical graph clustering for a collection of networks.
- R package missSOM released on CRAN. With Sara Rejeb and Catherine Duveau, 2021. Self-organizing maps with built-in missing-data imputation.
- R code for reproducibility of results of the article Graph inference with clustering and false discovery rate control. With Fanny Villers and Etienne Roquain, 2020.
- R package noisySBM released on CRAN. With Fanny Villers and Etienne Roquain, 2020. Implementation of the methods presented in the article Graph inference with clustering and false discovery rate control.
- R and Matlab code for the article Properties of the Stochastic Approximation EM Algorithm with Mini-batch Sampling. With Estelle Kuhn and Catherine Matias. Statistics and Computing (2020) tgz
- R code for the variational EM-algorithm for the Poisson process stochastic block model with Catherine Matias and Fanny Villers: ppsbm-files.zip This file contains the analysis of three datasets with PPSBM.
- R package ppsbm released on CRAN. With Daphné Giorgi, Catherine Matias and Fanny Villers, 2018. This package contains the optimized R code for PPSBM.
Enseignement
Formation continue
- Introduction au Machine Learning et au Deep Learning avec Python, Formation Entreprise CNRS. Prochaine édition : du 19 au 21 juin 2024. Voici la Page de la formation et la Fiche d'information
Notes de cours
- Analyse statistique de graphes, M2 de Statistique
- Probability Refresher, Master Data Science for Business, X-HEC
- Probabilités numériques et statistique computationnelle, M1, avec Vincent Lemaire
- Aléatoire - MAP361, Ecole polytechnique
- Statistical Modeling with R, Master in the Mathematical Sciences, AIMS Sénégal, 2018
- Statistique, 4M015, M1, version 2017, Partie II
- Statistique appliquée, M1, version 2015, Partie I et II
Notes de cours 2021 Book
Données pour les TP TP 1
Textbook pdf
Slides Chapter 1, Chapter 2 1st part, 2nd part, Chapter 3, Chapter 4, Chapter 5
Poly 2021 pdf
Notebook 6, Estimation de paramètres de la loi Gamma, NB6_sujet.ipynb, NB6_sujet.html
Notebook 7, Bootstrap, NB7_sujet.ipynb, NB7_sujet.html
Notebook 8, Le package boot, NB8_sujet.ipynb, NB8_sujet.html
Notebook 9, Modèle de mélange, NB9_sujet.ipynb, NB9_sujet.html
Notebook 10, Algorithme EM pour mélange gaussien, NB10_sujet.ipynb, NB10_sujet.html
Notebook 11, Echantillonneur de Gibbs pour mélange gaussien, NB11_sujet.ipynb, NB11_sujet.html
Feuilles d'exercices 2020 PC 1, PC 2, PC 3, PC 4, PC 5, PC 6, PC 7, PC 8, PC 9
Slides Chapter 1, Chapter 2, Chapter 3, Chapter 4, Chapter 5
Computer Labs Lab 1, Lab 2, Lab 3,
Exercises Series 1, Series 2, Series 3
Assignment zip
Notebooks d'anciens cours
- Statistique numérique (3M248)
Notebook 1, Rappels et prise en main, NB1_Series.ipynb, NB1_Series.html
Notebook 2, Tableaux de données, NB2_Dataframe.ipynb, NB2_Dataframe.html
Notebook 3, Figures, NB3_Figures.ipynb, NB3_Figures.html
Notebook 4, Statistique descriptive univariée, NB4_stat_descr_uni.ipynb, NB4_stat_descr_uni.html
Notebook 5, Statistique descriptive pour des données bivariées, NB5_stat_descr_bivarie.ipynb, NB5_stat_descr_bivarie.html
Notebook 6, Variables qualitatives et indépendance, NB6_variables_qualitatives.ipynb, NB6_variables_qualitatives.html
Notebook 7, Analyse en composantes principales, NB7_ACP.ipynb, NB7_ACP.html
Notebook 8, Interprétation de l'ACP, NB8_ACP_bis.ipynb, NB8_ACP_bis.html
- Statistique (4M015)
Prise en main de R pdf
Notebook 1, Notebook R, vecteurs et génération de variables aléatoires, Notebook_1.ipynb, Notebook_1.html
Notebook 2, Type de données, Notebook_2.ipynb, Notebook_2.html , Données zip
Notebook 3, Représentations graphiques des données, Notebook_3.ipynb, Notebook_3.html , données anorexie
Programmation en R pdf
Notebook 4, Simulations Monte-Carlo, Notebook_4.ipynb, Notebook_4.html
Notebook 5, Simulations Monte-Carlo (suite), Notebook_5.ipynb, Notebook_5.html
Notebook 6, Régression simple, Notebook_6.ipynb, Notebook_6.html , Données ozone, cathedral
Notebook 7, Régression multiple, Notebook_7.ipynb, Notebook_7.html , Données poidsnaiss
Notebook 8, Analyse de la variance, Notebook_8.ipynb, Notebook_8.html
Other
Exposé pour des jeunes mathématicien·ne·s
- Mathematic Park , exposé du 25 novembre 2023 intitulé Tous connectés sur les réseaux sociaux. Quels outils mathématiques pour les analyser ? Voici les slides et le notebook R